df <- read.csv("csv/20240805基本資料_retrospective.csv",
na.strings = c("", "NA"),
fileEncoding = "Big5")
dfsummary(df)## 編號 性別 慢性病用藥狀況.複選. Comorbidity.多選.
## Min. : 1 Length:6345 Length:6345 Length:6345
## 1st Qu.:1726 Class :character Class :character Class :character
## Median :3634 Mode :character Mode :character Mode :character
## Mean :3548
## 3rd Qu.:5279
## Max. :6971
## NA's :1
## 醫院代碼 術前主述.複選. Biopsy.date.確診日期.
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Biopsy.method.複選. Cell.Type 多發性 切片檢體腫瘤惡性度
## Length:6345 Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## 病理分期 危險因子..複選. 合併膀胱腫瘤 合併CIS
## Length:6345 Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## surgical.margin 左右側 腫瘤位置.多選. 腫瘤大小
## Length:6345 Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## 完整檢體腫瘤惡性度 pathological.stage 術前水腎
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Lymphovascular.invasion Tumor.Necrosis 有無針對UTUC化療
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## 針對UTUC化療型態 化療處方 NxUx.date
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## NxUx.Access.method..複選. Bladder.cuff.resection other.bladder.cuff.method
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Lymphadenectomy.位置.複選. simultaneously.ipsilateral.adrenalectomy
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## Post.operation.intravesical.C.T.instillation Endoscopic.resection.date
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## Endoscopic.Access.method Endoscopic.Energy.device..複選.
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## endoscopic.ablation.次數 post.ablation.Intra.cavitary.C.T
## Min. : 0.000 Length:6345
## 1st Qu.: 1.000 Class :character
## Median : 2.000 Mode :character
## Mean : 2.416
## 3rd Qu.: 3.000
## Max. :15.000
## NA's :5915
## Salvage.Nephroureterectomy date.of.salvage.NU date.of.segmental.resection
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Segmental.resection.Access.method..複選. salvage.Nephroureterectomy
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## Date.of.salvage.NU Clavien.Dindo.classification.複選.
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## complication.list..請填寫手術併發症中英文均可. 術後住院天數..day.
## Length:6345 Min. : 0.000
## Class :character 1st Qu.: 6.000
## Mode :character Median : 7.000
## Mean : 8.541
## 3rd Qu.: 9.000
## Max. :99.000
## NA's :2021
## Residual.bladder.cuff Date.of.last.cystoscopy
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## Bladder.UC.after.NUx.or.Endoscopic.or.Segmental.resection
## Length:6345
## Class :character
## Mode :character
##
##
##
##
## Date.of.Bladder.UC.recurrence.after.NUx.or.Endoscopic.or.Segmental.resection
## Length:6345
## Class :character
## Mode :character
##
##
##
##
## 患側Upper.ureter.or.renal.pelvis.local.recurrence
## Length:6345
## Class :character
## Mode :character
##
##
##
##
## Date.of.Upper.ureter.or.renal.pelvis.recurrence
## Length:6345
## Class :character
## Mode :character
##
##
##
##
## 患側Lower.ureter.or.bladder.cuff..local.recurrence
## Length:6345
## Class :character
## Mode :character
##
##
##
##
## Date.of.Lower.ureter.or.bladder.cuff.recurrence 淋巴轉移及位置..複選.
## Length:6345 Length:6345
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## Date.of.LN.mets 遠端轉移.複選. Date.of.distant.mets
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Disease.free.註.不含膀胱內復發. Mortality Date.of.mortality
## Length:6345 Length:6345 Length:6345
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## 長期.Complication 手術到死亡間隔時間..月. Post.OP.1.month.eGFR
## Length:6345 Min. : -51 Min. : 0.3898
## Class :character 1st Qu.: 11 1st Qu.:57.5790
## Mode :character Median : 29 Median : Inf
## Mean : 6254 Mean : Inf
## 3rd Qu.: 66 3rd Qu.: Inf
## Max. :16708534 Max. : Inf
## NA's :3653 NA's :79
## last.eGFR Lost.follow.up Longest.follow.up.month.for.BDFS.DFS
## Min. : 0.00 Length:6345 Min. : -1.61
## 1st Qu.:24.80 Class :character 1st Qu.: 12.42
## Median :54.41 Mode :character Median : 31.93
## Mean : Inf Mean : 43.21
## 3rd Qu.: Inf 3rd Qu.: 62.53
## Max. : Inf Max. :275.59
## NA's :43 NA's :326
## Longest.follow.up.month.for.OS.CSS 死亡檔最後追蹤日期 死亡檔最長追蹤時間.month
## Min. : 0.00 Length:6345 Min. : -51.35
## 1st Qu.: 20.86 Class :character 1st Qu.: 21.48
## Median : 51.41 Mode :character Median : 53.43
## Mean : 65.76 Mean : 66.14
## 3rd Qu.: 95.27 3rd Qu.: 94.84
## Max. :2023.10 Max. :2023.10
## NA's :52 NA's :1001
## ECOG ASA.score 身高..公分. 體重..公斤.
## Length:6345 Min. :1.000 Length:6345 Min. : 17.20
## Class :character 1st Qu.:2.000 Class :character 1st Qu.: 52.00
## Mode :character Median :3.000 Mode :character Median : 60.00
## Mean :2.581 Mean : 61.07
## 3rd Qu.:3.000 3rd Qu.: 68.00
## Max. :4.000 Max. :646.00
## NA's :2322 NA's :1858
## 生日 診斷年紀 術前Cr.level..mg.dl.
## Length:6345 Min. : 8.00 Length:6345
## Class :character 1st Qu.: 61.33 Class :character
## Mode :character Median : 69.18 Mode :character
## Mean : 68.31
## 3rd Qu.: 76.03
## Max. :101.72
## NA's :49colnames(df)## [1] "編號"
## [2] "性別"
## [3] "慢性病用藥狀況.複選."
## [4] "Comorbidity.多選."
## [5] "醫院代碼"
## [6] "術前主述.複選."
## [7] "Biopsy.date.確診日期."
## [8] "Biopsy.method.複選."
## [9] "Cell.Type"
## [10] "多發性"
## [11] "切片檢體腫瘤惡性度"
## [12] "病理分期"
## [13] "危險因子..複選."
## [14] "合併膀胱腫瘤"
## [15] "合併CIS"
## [16] "surgical.margin"
## [17] "左右側"
## [18] "腫瘤位置.多選."
## [19] "腫瘤大小"
## [20] "完整檢體腫瘤惡性度"
## [21] "pathological.stage"
## [22] "術前水腎"
## [23] "Lymphovascular.invasion"
## [24] "Tumor.Necrosis"
## [25] "有無針對UTUC化療"
## [26] "針對UTUC化療型態"
## [27] "化療處方"
## [28] "NxUx.date"
## [29] "NxUx.Access.method..複選."
## [30] "Bladder.cuff.resection"
## [31] "other.bladder.cuff.method"
## [32] "Lymphadenectomy.位置.複選."
## [33] "simultaneously.ipsilateral.adrenalectomy"
## [34] "Post.operation.intravesical.C.T.instillation"
## [35] "Endoscopic.resection.date"
## [36] "Endoscopic.Access.method"
## [37] "Endoscopic.Energy.device..複選."
## [38] "endoscopic.ablation.次數"
## [39] "post.ablation.Intra.cavitary.C.T"
## [40] "Salvage.Nephroureterectomy"
## [41] "date.of.salvage.NU"
## [42] "date.of.segmental.resection"
## [43] "Segmental.resection.Access.method..複選."
## [44] "salvage.Nephroureterectomy"
## [45] "Date.of.salvage.NU"
## [46] "Clavien.Dindo.classification.複選."
## [47] "complication.list..請填寫手術併發症中英文均可."
## [48] "術後住院天數..day."
## [49] "Residual.bladder.cuff"
## [50] "Date.of.last.cystoscopy"
## [51] "Bladder.UC.after.NUx.or.Endoscopic.or.Segmental.resection"
## [52] "Date.of.Bladder.UC.recurrence.after.NUx.or.Endoscopic.or.Segmental.resection"
## [53] "患側Upper.ureter.or.renal.pelvis.local.recurrence"
## [54] "Date.of.Upper.ureter.or.renal.pelvis.recurrence"
## [55] "患側Lower.ureter.or.bladder.cuff..local.recurrence"
## [56] "Date.of.Lower.ureter.or.bladder.cuff.recurrence"
## [57] "淋巴轉移及位置..複選."
## [58] "Date.of.LN.mets"
## [59] "遠端轉移.複選."
## [60] "Date.of.distant.mets"
## [61] "Disease.free.註.不含膀胱內復發."
## [62] "Mortality"
## [63] "Date.of.mortality"
## [64] "長期.Complication"
## [65] "手術到死亡間隔時間..月."
## [66] "Post.OP.1.month.eGFR"
## [67] "last.eGFR"
## [68] "Lost.follow.up"
## [69] "Longest.follow.up.month.for.BDFS.DFS"
## [70] "Longest.follow.up.month.for.OS.CSS"
## [71] "死亡檔最後追蹤日期"
## [72] "死亡檔最長追蹤時間.month"
## [73] "ECOG"
## [74] "ASA.score"
## [75] "身高..公分."
## [76] "體重..公斤."
## [77] "生日"
## [78] "診斷年紀"
## [79] "術前Cr.level..mg.dl."colnames(df) <- c("編號", "性別", "慢性病用藥狀況", "Comorbidity", "醫院代碼", "術前主述", "Biopsy_date_確診日期", "Biopsy_method", "Cell_Type", "多發性", "切片檢體腫瘤惡性度", "病理分期", "危險因子", "合併膀胱腫瘤", "合併CIS", "surgical_margin", "左右側", "腫瘤位置", "腫瘤大小", "完整檢體腫瘤惡性度", "pathological_stage", "術前水腎", "Lymphovascular_invasion", "Tumor_Necrosis", "有無針對UTUC化療", "針對UTUC化療型態", "化療處方", "NxUx_date", "NxUx_Access_method", "Bladder_cuff_resection", "other_bladder_cuff_method", "Lymphadenectomy_位置", "simultaneously_ipsilateral_adrenalectomy", "Post_operation_intravesical_CT_instillation", "Endoscopic_resection_date", "Endoscopic_Access_method", "Endoscopic_Energy_device", "endoscopic_ablation_次數", "post_ablation_Intra_cavitary_CT", "Salvage_Nephroureterectomy", "date_of_salvage_NU", "date_of_segmental_resection", "Segmental_resection_Access_method", "salvage_Nephroureterectomy", "Date_of_salvage_NU", "Clavien_Dindo_classification", "complication_list", "術後住院天數_天", "Residual_bladder_cuff", "Date_of_last_cystoscopy", "Bladder_UC_after_NUx_or_Endoscopic_or_Segmental_resection", "Date_of_Bladder_UC_recurrence_after_NUx_or_Endoscopic_or_Segmental_resection", "患側Upper_ureter_or_renal_pelvis_local_recurrence", "Date_of_Upper_ureter_or_renal_pelvis_recurrence", "患側Lower_ureter_or_bladder_cuff_local_recurrence", "Date_of_Lower_ureter_or_bladder_cuff_recurrence", "淋巴轉移及位置", "Date_of_LN_mets", "遠端轉移", "Date_of_distant_mets", "Disease_free", "Mortality", "Date_of_mortality", "長期_Complication", "手術到死亡間隔時間_月", "Post_OP_1_month_eGFR", "last_eGFR", "Lost_follow_up", "Longest_follow_up_month_for_BDFS_DFS", "Longest_follow_up_month_for_OS_CSS", "死亡檔最後追蹤日期", "死亡檔最長追蹤時間_月", "ECOG", "ASA", "身高", "體重", "生日", "診斷年紀", "術前Cr_level_mg_dl")0.4 drop missing rows
n_missing <- c()
for(i in 1:6345){
if(sum(1*is.na(df[i,]))>50){
n_missing <- c(n_missing, i)
}
}
df1 <- df[-n_missing,]library(dplyr)select()df2 <- df1%>%
dplyr::select(編號, 性別, ECOG, 身高, 體重, 生日, Comorbidity, 腫瘤位置, 腫瘤大小, pathological_stage, Mortality, Date_of_mortality, 術前Cr_level_mg_dl, Post_OP_1_month_eGFR, 死亡檔最長追蹤時間_月)
df2df3 <- df2%>%
transform(性別 = as.factor(性別))%>%
transform(ECOG = as.factor(ECOG))%>%
transform(身高 = as.numeric(身高))%>%
transform(體重 = as.numeric(體重))%>%
transform(生日 = as.Date(生日, "%m/%d/%Y"))%>%
transform(Comorbidity = as.factor(Comorbidity))%>%
transform(腫瘤位置 = as.factor(腫瘤位置))%>%
transform(腫瘤大小 = as.factor(腫瘤大小))%>%
transform(pathological_stage = as.factor(pathological_stage))%>%
transform(Mortality = as.factor(Mortality))%>%
transform(Date_of_mortality = as.Date(Date_of_mortality, "%m/%d/%Y"))%>%
transform(術前Cr_level_mg_dl = as.numeric(術前Cr_level_mg_dl))%>%
transform(Post_OP_1_month_eGFR = as.numeric(Post_OP_1_month_eGFR))%>%
transform(死亡檔最長追蹤時間_月 = as.numeric(死亡檔最長追蹤時間_月))## Warning in eval(substitute(list(...)), `_data`, parent.frame()): NAs introduced
## by coercion
## Warning in eval(substitute(list(...)), `_data`, parent.frame()): NAs introduced
## by coerciondf3df2%>%
transform(性別 = as.factor(性別))%>%
transform(ECOG = as.factor(ECOG))%>%
transform(Comorbidity = as.factor(Comorbidity))%>%
transform(腫瘤位置 = as.factor(腫瘤位置))%>%
transform(腫瘤大小 = as.factor(腫瘤大小))%>%
transform(pathological_stage = as.factor(pathological_stage))%>%
transform(Mortality = as.factor(Mortality))%>%
dplyr::select(性別, ECOG, Comorbidity, 腫瘤位置, pathological_stage, Mortality)df2%>%
transform(身高 = as.numeric(身高))%>%
transform(體重 = as.numeric(體重))%>%
transform(術前Cr_level_mg_dl = as.numeric(術前Cr_level_mg_dl))%>%
transform(Post_OP_1_month_eGFR = as.numeric(Post_OP_1_month_eGFR))%>%
transform(死亡檔最長追蹤時間_月 = as.numeric(死亡檔最長追蹤時間_月))%>%
dplyr::select(身高, 體重, 術前Cr_level_mg_dl, Post_OP_1_month_eGFR, 死亡檔最長追蹤時間_月)## Warning in eval(substitute(list(...)), `_data`, parent.frame()): NAs introduced
## by coercion
## Warning in eval(substitute(list(...)), `_data`, parent.frame()): NAs introduced
## by coerciondf2%>%
transform(生日 = as.Date(生日, "%m/%d/%Y"))%>%
transform(Date_of_mortality = as.Date(Date_of_mortality, "%m/%d/%Y"))%>%
select(生日, Date_of_mortality)df3summary()summary(df3)## 編號 性別 ECOG 身高
## Min. : 1 1 男:2731 0 無症狀 :2090 Min. :128.0
## 1st Qu.:1701 2 女:3539 1 有症狀,可步行對生活不影響:1799 1st Qu.:152.0
## Median :3604 2 躺在床上時間小於50% : 324 Median :158.0
## Mean :3518 3 躺在床上時間大於50% : 48 Mean :158.1
## 3rd Qu.:5232 4 完全臥床 : 15 3rd Qu.:164.0
## Max. :6961 NA's :1994 Max. :189.0
## NA's :1825
## 體重 生日
## Min. : 17.20 Min. :1907-10-01
## 1st Qu.: 52.00 1st Qu.:1936-07-01
## Median : 60.00 Median :1943-11-19
## Mean : 61.08 Mean :1944-07-17
## 3rd Qu.: 68.00 3rd Qu.:1952-04-15
## Max. :646.00 Max. :1992-12-20
## NA's :1797 NA's :621
## Comorbidity 腫瘤位置
## 0 none :1248 1 腎盂 :2564
## 5 HTN : 744 4 下輸尿管 : 808
## 5 HTN, 10 DM : 411 2 上輸尿管 : 653
## 10 DM : 201 3 中輸尿管 : 520
## 16 malignancy (非UTUC/ bladder UC): 144 1 腎盂, 2 上輸尿管: 511
## (Other) :3062 (Other) :1210
## NA's : 460 NA's : 4
## 腫瘤大小 pathological_stage Mortality
## 4 ? 3cm :2238 4 pT3, 9 pNx:1035 0 no :2781
## 3 ?2 & < 3 cm: 552 2 pT1, 9 pNx:1027 1 UTUC related :1244
## 2 ?1 & < 2 cm: 519 3 pT2, 9 pNx: 743 2 non-UTUC related:1218
## 3 ?2 & < 3 cm : 505 9 pNx, 1 pTa: 655 3 Nonknown : 567
## 2 ?1 & < 2 cm : 497 4 pT3, 6 pN0: 333 3 死因不明 : 259
## (Other) : 910 (Other) :1697 (Other) : 179
## NA's :1049 NA's : 780 NA's : 22
## Date_of_mortality 術前Cr_level_mg_dl Post_OP_1_month_eGFR
## Min. :1989-02-10 Min. : 0.190 Min. : 0.3898
## 1st Qu.:2012-03-22 1st Qu.: 1.000 1st Qu.:57.1777
## Median :2016-04-03 Median : 1.350 Median : Inf
## Mean :2014-09-08 Mean : 2.361 Mean : Inf
## 3rd Qu.:2019-01-14 3rd Qu.: 2.100 3rd Qu.: Inf
## Max. :2024-06-12 Max. :21.860 Max. : Inf
## NA's :3583 NA's :565 NA's :77
## 死亡檔最長追蹤時間_月
## Min. : -51.35
## 1st Qu.: 21.53
## Median : 53.50
## Mean : 66.16
## 3rd Qu.: 94.81
## Max. :2023.10
## NA's :932df4 <- df3%>%
mutate(BMI = factor(ifelse(is.na(身高)|is.na(體重),
NA,
ifelse(體重/(身高/100)^2<25,
"0 Normal", "1 Overweight"))),
.after = 體重)%>%
dplyr::select(-身高, -體重)%>%
mutate(Comorbidity = as.factor(
ifelse(is.na(Comorbidity), NA,
ifelse(grepl("5 HTN", Comorbidity),
"1 HTN",
"0 No HTN"))
))%>%
mutate(腫瘤位置 = as.factor(
ifelse(is.na(腫瘤位置), "5 無法識別",
ifelse(腫瘤位置=="0 non-visible", "0 non-visible",
ifelse(腫瘤位置=="1 腎盂", "1 腎盂",
ifelse(腫瘤位置=="2 上輸尿管"|
腫瘤位置=="3 中輸尿管"|
腫瘤位置=="4 下輸尿管"|
腫瘤位置=="6 Urerter, unknown site", "2 輸尿管",
ifelse(腫瘤位置=="5 膀胱袖口", "3 膀胱袖口",
ifelse(腫瘤位置=="7 Not available", "5 無法識別",
"4 多個位置"))))))
))%>%
mutate(腫瘤大小 = as.factor(
ifelse(is.na(腫瘤大小)|腫瘤大小=="Not available", "0 Not available",
ifelse(grepl(3,腫瘤大小)|grepl(4,腫瘤大小), "2 >=2cm", "1 <2cm"))
))%>%
mutate(pT = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("T0", pathological_stage)|
grepl("Tis", pathological_stage)|
grepl("Ta", pathological_stage), "1 T0/Tis/Ta",
ifelse(grepl("T1", pathological_stage), "2 T1",
ifelse(grepl("T2", pathological_stage), "3 T2",
ifelse(grepl("T3", pathological_stage), "4 T3",
ifelse(grepl("T4", pathological_stage), "5 T4", "0 None"))))))
),
.after = pathological_stage)%>%
mutate(pN = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("9 ", pathological_stage), "1 Nx",
ifelse(grepl("6 ", pathological_stage), "2 N0",
ifelse(grepl("7 ", pathological_stage), "3 N1",
ifelse(grepl("8 ", pathological_stage), "4 N2", "0 None")))))
),
.after = pT)%>%
mutate(pM = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("12 ", pathological_stage), "1 M0",
ifelse(grepl("11 ", pathological_stage), "2 M1", "0 None")))
),
.after = pN)%>%
dplyr::select(-pathological_stage)%>%
mutate(Mortality = as.factor(
ifelse(is.na(Mortality),
NA,
ifelse(grepl(0, Mortality),
"0 No",
ifelse(grepl(1, Mortality),
"1 UTUC related",
ifelse(grepl(2, Mortality),
"2 Non-UTUC related",
ifelse(grepl(3, Mortality),
"3 死因不明",
ifelse(grepl(4, Mortality),
"4 Surgery related", NA))))))
))%>%
mutate(Age_of_Mortality = ifelse(is.na(Date_of_mortality)|is.na(生日), NA,
as.numeric(difftime(Date_of_mortality,
生日))),
.after = Date_of_mortality)%>%
mutate(Age_of_Mortality = round(Age_of_Mortality/365, 0))
df4mutate()ifelse()
is.na()grepl()round()df3%>%
mutate(BMI = round(體重/(身高/100)^2, digits = 2),
.after = 體重)%>%
mutate(BMI.group = factor(ifelse(is.na(身高)|is.na(體重),
NA,
ifelse(體重/(身高/100)^2<25,
"Normal", "Overweight"))),
.after = BMI)%>%
dplyr::select(身高, 體重, BMI, BMI.group)df3%>%
mutate(Comorbidity.HTN = as.factor(
ifelse(is.na(Comorbidity), NA,
ifelse(grepl("5 HTN", Comorbidity),
"1 HTN",
"0 No HTN"))
))%>%
dplyr::select(Comorbidity, Comorbidity.HTN)df3%>%
mutate(腫瘤位置.group = as.factor(
ifelse(is.na(腫瘤位置), "5 無法識別",
ifelse(腫瘤位置=="0 non-visible", "0 non-visible",
ifelse(腫瘤位置=="1 腎盂", "1 腎盂",
ifelse(腫瘤位置=="2 上輸尿管"|
腫瘤位置=="3 中輸尿管"|
腫瘤位置=="4 下輸尿管"|
腫瘤位置=="6 Urerter, unknown site", "2 輸尿管",
ifelse(腫瘤位置=="5 膀胱袖口", "3 膀胱袖口",
ifelse(腫瘤位置=="7 Not available", "5 無法識別",
"4 多個位置"))))))
))%>%
dplyr::select(腫瘤位置, 腫瘤位置.group)df3%>%
mutate(腫瘤大小.2cm = as.factor(
ifelse(is.na(腫瘤大小)|腫瘤大小=="Not available", "0 Not available",
ifelse(grepl(3,腫瘤大小)|grepl(4,腫瘤大小), "2 >=2cm", "1 <2cm"))
))%>%
dplyr::select(腫瘤大小, 腫瘤大小.2cm)df3%>%
mutate(pT = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("T0", pathological_stage)|
grepl("Tis", pathological_stage)|
grepl("Ta", pathological_stage), "T0/Tis/Ta",
ifelse(grepl("T1", pathological_stage), "T1",
ifelse(grepl("T2", pathological_stage), "T2",
ifelse(grepl("T3", pathological_stage), "T3",
ifelse(grepl("T4", pathological_stage), "T4", "None"))))))
),
.after = pathological_stage)%>%
mutate(pN = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("9 ", pathological_stage), "Nx",
ifelse(grepl("6 ", pathological_stage), "N0",
ifelse(grepl("7 ", pathological_stage), "N1",
ifelse(grepl("8 ", pathological_stage), "N2", "None")))))
),
.after = pT)%>%
mutate(pM = as.factor(
ifelse(is.na(pathological_stage), NA,
ifelse(grepl("12 ", pathological_stage), "M0",
ifelse(grepl("11 ", pathological_stage), "M1", "None")))
),
.after = pN)%>%
dplyr::select(pathological_stage, pT, pN, pM)df3%>%
mutate(Mortality.na = as.factor(
ifelse(is.na(Mortality),
NA,
ifelse(grepl(0, Mortality),
"0 No",
ifelse(grepl(1, Mortality),
"1 UTUC related",
ifelse(grepl(2, Mortality),
"2 Non-UTUC related",
ifelse(grepl(3, Mortality),
"3 死因不明",
ifelse(grepl(4, Mortality),
"4 Surgery related", NA))))))
))%>%
dplyr::select(Mortality, Mortality.na)df3%>%
mutate(Age_of_Mortality = ifelse(is.na(Date_of_mortality)|is.na(生日), NA,
as.numeric(difftime(Date_of_mortality,
生日))),
.after = Date_of_mortality)%>%
mutate(Age_of_Mortality = round(Age_of_Mortality/365, 0))%>%
dplyr::select(生日, Date_of_mortality, Age_of_Mortality)df5 <- df4%>%
filter(if_all(everything(), ~ !is.na(.)))
df5df6 <- df5%>%
select(編號, 性別, ECOG, BMI, Comorbidity, 腫瘤位置, 腫瘤大小, pT, pN, pM, Mortality, 死亡檔最長追蹤時間_月)%>%
mutate(編號 = as.numeric(gsub(".*?([0-9]+).*", "\\1", 編號)))%>%
mutate(性別 = as.numeric(gsub(".*?([0-9]+).*", "\\1", 性別)))%>%
mutate(ECOG = as.numeric(gsub(".*?([0-9]+).*", "\\1", ECOG)))%>%
mutate(BMI = as.numeric(gsub(".*?([0-9]+).*", "\\1", BMI)))%>%
mutate(Comorbidity = as.numeric(gsub(".*?([0-9]+).*", "\\1", Comorbidity)))%>%
mutate(腫瘤位置 = as.numeric(gsub(".*?([0-9]+).*", "\\1", 腫瘤位置)))%>%
mutate(腫瘤大小 = as.numeric(gsub(".*?([0-9]+).*", "\\1", 腫瘤大小)))%>%
mutate(pT = as.numeric(gsub(".*?([0-9]+).*", "\\1", pT)))%>%
mutate(pN = as.numeric(gsub(".*?([0-9]+).*", "\\1", pN)))%>%
mutate(pM = as.numeric(gsub(".*?([0-9]+).*", "\\1", pM)))%>%
mutate(Mortality = as.numeric(gsub(".*?([0-9]+).*", "\\1", Mortality)))%>%
mutate(死亡檔最長追蹤時間_月 = as.numeric(gsub(".*?([0-9]+).*", "\\1", 死亡檔最長追蹤時間_月)))
df6df5summary()summary(df5)## 編號 性別 ECOG
## Min. : 4.0 1 男:519 0 無症狀 :499
## 1st Qu.: 954.8 2 女:579 1 有症狀,可步行對生活不影響:468
## Median :3221.5 2 躺在床上時間小於50% :111
## Mean :3262.5 3 躺在床上時間大於50% : 15
## 3rd Qu.:4929.0 4 完全臥床 : 5
## Max. :6961.0
## BMI 生日 Comorbidity 腫瘤位置
## 0 Normal :699 Min. :1913-11-22 0 No HTN:406 0 non-visible: 1
## 1 Overweight:399 1st Qu.:1936-03-05 1 HTN :692 1 腎盂 :370
## Median :1942-04-25 2 輸尿管 :368
## Mean :1943-08-14 3 膀胱袖口 : 5
## 3rd Qu.:1950-10-26 4 多個位置 :353
## Max. :1989-07-25 5 無法識別 : 1
## 腫瘤大小 pT pN pM
## 0 Not available: 13 0 None : 1 0 None: 1 0 None:971
## 1 <2cm :251 1 T0/Tis/Ta:134 1 Nx :794 1 M0 :122
## 2 >=2cm :834 2 T1 :200 2 N0 :213 2 M1 : 5
## 3 T2 :196 3 N1 : 31
## 4 T3 :461 4 N2 : 59
## 5 T4 :106
## Mortality Date_of_mortality Age_of_Mortality
## 0 No : 7 Min. :2007-06-14 Min. : 31.00
## 1 UTUC related :484 1st Qu.:2016-01-20 1st Qu.: 68.00
## 2 Non-UTUC related:496 Median :2018-05-09 Median : 75.00
## 3 死因不明 : 85 Mean :2017-11-10 Mean : 74.31
## 4 Surgery related : 26 3rd Qu.:2020-03-25 3rd Qu.: 82.00
## Max. :2024-06-12 Max. :103.00
## 術前Cr_level_mg_dl Post_OP_1_month_eGFR 死亡檔最長追蹤時間_月
## Min. : 0.470 Min. : 2.049 Min. : 0.0657
## 1st Qu.: 1.080 1st Qu.:43.973 1st Qu.: 10.6932
## Median : 1.485 Median : Inf Median : 26.7411
## Mean : 2.625 Mean : Inf Mean : 35.5088
## 3rd Qu.: 2.895 3rd Qu.: Inf 3rd Qu.: 49.3183
## Max. :21.860 Max. : Inf Max. :170.5322df6summary()summary(df6)## 編號 性別 ECOG BMI
## Min. : 4.0 Min. :1.000 Min. :0.0000 Min. :0.0000
## 1st Qu.: 954.8 1st Qu.:1.000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :3221.5 Median :2.000 Median :1.0000 Median :0.0000
## Mean :3262.5 Mean :1.527 Mean :0.6876 Mean :0.3634
## 3rd Qu.:4929.0 3rd Qu.:2.000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :6961.0 Max. :2.000 Max. :4.0000 Max. :1.0000
## Comorbidity 腫瘤位置 腫瘤大小 pT
## Min. :0.0000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000
## Median :1.0000 Median :2.000 Median :2.000 Median :4.000
## Mean :0.6302 Mean :2.311 Mean :1.748 Mean :3.184
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:2.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :2.000 Max. :5.000
## pN pM Mortality 死亡檔最長追蹤時間_月
## Min. :0.000 Min. :0.0000 Min. :0.000 Min. : 0.00
## 1st Qu.:1.000 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.: 10.00
## Median :1.000 Median :0.0000 Median :2.000 Median : 26.00
## Mean :1.411 Mean :0.1202 Mean :1.671 Mean : 35.01
## 3rd Qu.:2.000 3rd Qu.:0.0000 3rd Qu.:2.000 3rd Qu.: 49.00
## Max. :4.000 Max. :2.0000 Max. :4.000 Max. :170.00